Open-World object detection/segmentation.
Open-world recognition problems are gaining attention in image classification, object detection, and segmentation [1]}, [2]}, [3]}.
Especially, many methods have been proposed for open-set image classification, where the goal is to separate novel categories from known categories given a closed-set training set [1]}, [5]}, [6]}, [7]}, [8]}. On the contrary, the goal of open-world instance segmentation is to detect and segment all objects in a scene without distinguishing novel objects from seen ones. We acknowledge that there is ambiguity in the definition of “object”, and follow [9]} during evaluation.
